Rosen, a researcher at the Stanford Research Institute in Menlo Park, California, envisioned a roboperson driven by neural networks, algorithms that mimic the human brain. Much like its biological counterparts, it would have the power to see and sense its environment. As Rosen and his team wrote in a memo (.pdf) to DARPA, the Defense Department’s research arm, describing the project, it would “perform reconnaissance missions” that would normally require human intelligence.

DARPA eventually “got kind of excited about it,” recalls Nils Nilsson, one of the leaders of the project, and the agency granted the researchers $750,000 — more than $5 million in today’s money — to make it happen.

The project didn’t include true neutral networks — in the 1960s, the technology just wasn’t up to the sort of visual analysis, planning, and navigation Rosen and team wanted to explore — but the automaton did indeed happen. And it could see and move and respond to its environment in at least some basic ways. It looked kinda like the one-eyed, four-wheeled, armless spawn of Wall-E and Rosie the Robot. His name was Shakey, because, well, he shook a lot as he rolled around.

Shakey was a seminal creation in the world of artificial intelligence, a big step along the road to everything from natural language processing to computer games. And he was an awful lot of fun.

A radio antenna sat atop Shakey’s head, wirelessly connecting his body to his remote brain, a room-sized Digital Equipment Corporation PDP-10 mainframe computer. The PDP-10 housed most of the code used to control Shakey, including the visual processing software that analyzed data gathered by the single television camera attached to his elongated head and his “cat whisker” sensors — long, wiry extensions located near his base that let Shakey know if he bumped into something.

If he ran into something small and light enough, he could even push it aside with a kind of mechanical arm.

“Our goal is to give Shakey some of the abilities associated with intelligence, abilities like planning and learning,” we heard in the official Shakey video below. “The main purpose of our research is to learn how to design these programs so that robots can be employed in a variety of tasks, ranging from space exploration to industrial automation.”

Shakey would never make it to the moon or even into a factory. But considering he had access to less computational power than your iPhone, he was pretty adept at dealing with unpredictable circumstances as he rolled his way from place to place.

He uses a three-tiered software architecture that divided his behavior into low-, intermediate- and high-level actions. Low-level actions were analogous to reflexes — simple movements like moving forward or moving his camera eye. Executed in tandem, these could then deliver intermediate-level actions, such as pushing an object across a surface, and thanks to Shakey’s planning system, called STRIPS, the intermediate actions could help complete higher-level tasks, like getting from one room to another while dealing with unexpected obstacles.

“If Charlie the Gremlin came and did something upsetting, STRIPS could cook up a new plan,” says Nilsson. “It was a really complex program for its day.” Charlie the Gremlin would be the alter ego of Charles Rosen. In the official video, you can see him and his flowing cape in all their devious glory.

“It really stands as a milestone in the evolution of robotics, artificial intelligence and machine learning.”

— Peter Hart

Shakey could navigate his simple, controlled environment thanks to a dynamic map stored on the PDP-10. If Shakey lost his bearings, he could scan the room with his TV-camera eye and, through some simple geometry, figure out where he was.

“It was the first mobile, intelligent robot,” said Peter Hart, who worked on Shakey from the start of the project. “It really stands as a milestone in the evolution of robotics, artificial intelligence and machine learning. It seems almost quaint by modern standards, but it really was the first of an era.”

The Shakey project came to a close in 1972 when DARPA funding dried up. But Shakey’s legacy lives on. He inspired a generation of computer scientists and engineers to “take mobile intelligent robots seriously,” says Hart.

Some techniques developed for Shakey, including tech behind its A* navigation and STRIPS programs, still play a role in today’s natural language processing tools, computer games, and other applications. You can find them in route-finding applications such as Google Maps, car navigation systems, and even the Curiosity rover now on Mars. These techniques have also played a role in planning experiments on the Hubble Space Telescope, says Nilsson, who happened to be visiting Hart, an old friend and Shakey colleague, when he spoke to WIRED.

Shakey currently lives at the Computer History Museum in Mountain View, California. He was inducted to the Robot Hall of Fame, together with C-3PO, in 2004.